Jeawak, Shelan, Jones, Christopher  ORCID: https://orcid.org/0000-0001-6847-7575 and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881
2019.
Embedding geographic locations for modelling the natural environment using Flickr tags and structured data.
Presented at: ECIR 2019: 41st European Conference on Information Retrieval,
Cologne, Germany,
14-18 April 2019.
Published in: Azzopardi, L., Stein, B., Fuhr, N., Mayr, P., Hauff, C. and Hiemstra, D. eds.
Advances in Information Retrieval: 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14–18, 2019, Proceedings, Part I.
Lecture Notes in Computer Science.
, vol.1
Springer,
pp. 51-66.
10.1007/978-3-030-15712-8_4
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Abstract
Meta-data from photo-sharing websites such as Flickr can be used to obtain rich bag-of-words descriptions of geographic locations, which have proven valuable, among others, for modelling and predicting ecological features. One important insight from previous work is that the descriptions obtained from Flickr tend to be complementary to the structured information that is available from traditional scientific resources. To better integrate these two diverse sources of information, in this paper we consider a method for learning vector space embeddings of geographic locations. We show experimentally that this method improves on existing approaches, especially in cases where structured information is available.
| Item Type: | Conference or Workshop Item - published (Paper) |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Professional Services > Advanced Research Computing @ Cardiff (ARCCA) Schools > Computer Science & Informatics |
| Publisher: | Springer |
| ISBN: | 978-3-030-15711-1 |
| ISSN: | 0302-9743 |
| Related URLs: | |
| Date of First Compliant Deposit: | 14 February 2019 |
| Last Modified: | 13 May 2026 09:00 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/119323 |
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